open source pkg v1

dbm_lib/dbm_features/raw_features/util/util.py

@@ -0,0 +1,112 @@
+"""
+file_name: util
+project_name: DBM
+created: 2020-20-07
+"""
+
+import os
+import glob
+import numpy as np
+import subprocess
+
+def filter_path(video_url, out_dir):
+    
+    """
+    Filtering video uri path to prepare input and ouptut location
+    
+    Args:
+        video_url: S3 bucket path for video
+        out_dir: Output directory path
+        
+    """
+    
+    fl_name,_ = os.path.splitext(os.path.basename(video_url))
+    input_loc = os.path.dirname(video_url)
+    out_loc = os.path.join(out_dir, fl_name)
+    return input_loc, out_loc, fl_name
+
+def save_output(df, out_loc, fl_name, f_dir, f_ext):
+    """
+    creating output directory for Audio features
+    Args:
+        df: (dataframe) feature dataframe[ex: Formant freq, pitch]
+        out_loc: (dir) Output location where we want to save raw output
+        fl_name: file name
+        f_dir: directory name for a feature
+        f_ext: extension for a feature [ex: '_pose.csv']
+    """
+    full_f_name = fl_name + f_ext
+    dir_path = os.path.join(out_loc, f_dir)
+    
+    if not os.path.exists(dir_path):
+        os.makedirs(dir_path)
+        
+    sav_path = os.path.join(dir_path,full_f_name)
+    df.to_csv(sav_path, index=False)
+
+def audio_process(base_dir,video_url):
+    """
+    Parsing cleaned audio files(Audio files without IMA voice)
+    Args:
+        base_dir: Base path for raw data
+        video_url: Raw video file path
+    """
+    new_video_url = base_dir+'/'.join(video_url[2:])
+    split_val = new_video_url.split('/')
+    wav_path = '/'.join(split_val[0:len(split_val)-1])
+    audio_split_check = glob.glob(wav_path + '/*_split.wav')
+    return audio_split_check
+
+def compute_open_face_features(input_filepath,
+                         output_directory,
+                         open_face_executable,
+                         au_static=False,
+                         tracked_visualization=False,
+                         clobber=False,
+                         verbose=True):
+    """
+    Runs OpenFace on an input video.
+    See https://github.com/TadasBaltrusaitis/OpenFace/wiki/Command-line-arguments
+    Args:
+        input_filepath:
+        output_directory:
+        au_static:
+        tracked_visualization:
+        open_face_executable:
+        clobber: (bool) if True existing files will be overwritten
+        verbose:
+    Returns:
+        (str) path to output csv file
+    Raises:
+        IOError if OpenFace executable is missing
+    """
+
+    if not os.path.isfile(open_face_executable):
+        raise IOError("OpenFace executable {} could not be found.".format(open_face_executable))
+
+    bn, _ = os.path.splitext(os.path.basename(input_filepath))
+    if not output_directory:
+        output_directory = os.path.join(os.path.dirname(input_filepath), bn + '_OF_features')
+
+    output_csv = os.path.join(output_directory, bn + '.csv')
+    if not os.path.isfile(output_csv) or clobber:
+        call = [open_face_executable, ]
+        if au_static:
+            call += ['-au_static', ]
+
+        if tracked_visualization:
+            call += ['-tracked', ]
+
+        call += ['-q', '-2Dfp', '-3Dfp', '-pdmparams', '-pose', '-aus', '-gaze']
+        call += ['-f', input_filepath, '-out_dir', output_directory]
+
+        if verbose:
+            print('Computing OpenFace features {} from video file'.format(input_filepath))
+        subprocess.check_output(call)
+        if verbose:
+            print('OpenFace features saved to {}'.format(output_directory))
+    else:
+        if verbose:
+            print('Output file {} already exists'.format(output_csv))
+
+    return os.path.join(output_directory, bn + '.csv')